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The mortality rate of oesophageal squamous cell carcinoma (ESCC) remains high, and conventional TNM systems cannot accurately predict its prognosis, thus necessitating a predictive model. In this study, a 17‐gene prognosis‐related gene signature (PRS) predictive model was constructed using the random survival forest algorithm as the optimal algorithm among 99 machine‐learning algorithm combinations based on data from 260 patients obtained from TCGA and GEO. The PRS model consistently outperformed other clinicopathological features and previously published signatures with superior prognostic accuracy, as evidenced by the receiver operating characteristic curve, C‐index and decision curve analysis in both training and validation cohorts. In the Cox regression analysis, PRS score was an independent adverse prognostic factor. The 17 genes of PRS were predominantly expressed in malignant cells by single‐cell RNA‐seq analysis via the TISCH2 database. They were involved in immunological and metabolic pathways according to GSEA and GSVA. The high‐risk group exhibited increased immune cell infiltration based on seven immunological algorithms, accompanied by a complex immune function status and elevated immune factor expression. Overall, the PRS model can serve as an excellent tool for overall survival prediction in ESCC and may facilitate individualized treatment strategies and predction of immunotherapy for patients with ESCC. [ABSTRACT FROM AUTHOR]

Currently, therapy response cannot be accurately predicted in HER2-negative breast cancer (BC). Measuring stromal tumour-infiltrating lymphocytes (sTILs) and mediators of the tumour microenvironment and characterizing tumour-infiltrating immune cells (TIICs) may improve treatment response in the neoadjuvant setting. Tumour tissue and peripheral blood samples were retrospectively collected from 118 patients, and sTILs were evaluated. Circulating exosomes and myeloid-derived suppressor cells were determined by flow cytometry. TIICs markers (CD4, CD8, CD20, CD1a, and CD68) were assessed immunohistochemically. High sTILs were significantly associated with pathological complete response (pCR; p = 0.048) and event-free survival (EFS; p = 0.027). High-CD68 cells were significantly associated with pCR in triple-negative (TN, p = 0.027) and high-CD1a cells with EFS in luminal-B (p = 0.012) BC. Cluster analyses of TIICs revealed two groups of tumours (C1 and C2) that had different immune patterns and clinical outcomes. An immunoscore based on clinicopathological variables was developed to identify high risk (C1) or low-risk (C2) patients. Additionally, cluster analyses revealed two groups of tumours for both luminal-B and TNBC. Our findings support the association of sTILs with pCR and show an immunological component in a subset of patients with HER2-negative BC. Our immunoscore may be useful for future escalation or de-escalation treatments. [ABSTRACT FROM AUTHOR]

Introduction: Regulator of G protein signalling 1 (RGS1) closely regulates malignant phenotypes and tumour immunity in several cancers, while its clinical value in nonsmall cell lung cancer (NSCLC) is by far rarely reported. Consequently, this study aimed to explore the linkage of blood RGS1 with clinical features and prognosis in surgical NSCLC patients. Methods: Two‐hundred and ten surgical NSCLC patients were consecutively enrolled in this study, whose RGS1 in peripheral blood mononuclear cells was determined before treatment via reverse transcriptional‐quantitative polymerase chain reaction. Additionally, the blood RGS1 was also collected from 30 healthy controls (HCs). Results: Blood RGS1 was increased in NSCLC patients compared with HCs (P < 0.001). Elevated blood RGS1 was related to lymph node (LYN) metastasis (P = 0.001), higher tumour‐nodes‐metastasis (TNM) stage (P = 0.004), neoadjuvant chemotherapy administration (P = 0.044), shortened accumulative disease‐free survival (DFS) (P = 0.008) and overall survival (OS) (P = 0.013) in NSCLC patients. A multivariate Cox's regression analysis showed that blood RGS1 high expression could independently reflect shortened DFS (hazard ratio = 1.499, P = 0.023), whereas it could not independently predict OS (P > 0.050). Furthermore, blood RGS1 high expression was associated with shortened OS (P = 0.020) in patients with neoadjuvant therapy and with worse DFS (P = 0.028) and OS (P = 0.026) in patients with adjuvant therapy, while blood RGS1 was not linked with DFS or OS in patients without neoadjuvant or adjuvant therapy (all P > 0.050). Conclusion: Elevated blood RGS1 correlates with LYN metastasis, neoadjuvant chemotherapy administration, worse DFS and OS, which might serve as a useful prognostic biomarker for surgical NSCLC patients. [ABSTRACT FROM AUTHOR]

Abstract Introduction Regulator of G protein signalling 1 (RGS1) closely regulates malignant phenotypes and tumour immunity in several cancers, while its clinical value in nonsmall cell lung cancer (NSCLC) is by far rarely reported. Consequently, this study aimed to explore the linkage of blood RGS1 with clinical features and prognosis in surgical NSCLC patients. Methods Two‐hundred and ten surgical NSCLC patients were consecutively enrolled in this study, whose RGS1 in peripheral blood mononuclear cells was determined before treatment via reverse transcriptional‐quantitative polymerase chain reaction. Additionally, the blood RGS1 was also collected from 30 healthy controls (HCs). Results Blood RGS1 was increased in NSCLC patients compared with HCs (P 0.050). Furthermore, blood RGS1 high expression was associated with shortened OS (P = 0.020) in patients with neoadjuvant therapy and with worse DFS (P = 0.028) and OS (P = 0.026) in patients with adjuvant therapy, while blood RGS1 was not linked with DFS or OS in patients without neoadjuvant or adjuvant therapy (all P > 0.050). Conclusion Elevated blood RGS1 correlates with LYN metastasis, neoadjuvant chemotherapy administration, worse DFS and OS, which might serve as a useful prognostic biomarker for surgical NSCLC patients.

Objective　 To screen out the prognosis-related genes in diffuse large B-cell lymphoma (DLBCL) and to confirm the relationship between the expression of prognosis-related genes and patients' survival and the proportion of tu⁃ mour-infiltrating immune cells (TICs) to provide new targets for the treatment and prognosis of DLBCL. Methods　 GSE56315, GSE12453 and GSE87371 microarray data were obtained from GEO, and DLBCL prognosis-associated genes were screened using the R "limma" package. Prognosis-related genes were analyzed for survival, independent prognosis, and correlation between prognosis-related gene expression levels and clinical parameters. The target genes in the GSE87371 datasets were categorised into high and low expression groups according to their median expression values, and the 5-year OS rates and 95%CIs of the high and low expression groups were extracted from the "survival" package in R. The correlation between the target genes and prognosis was then analyzed using COX risk regression models. Finally, "for loop" was used to analyse the relationship between the target gene and clinical parameters such as age, gender and clinical stage of DLBCL patients. The functional pathways of DLBCL prognosis-related genes in DLBCL were analyzed by GSEA enrichment. Finally, the CIBERSORT algorithm was used to calculate the proportion of TICs in DLBCL tis⁃ sues and to analyse the relationship between the expression levels of prognosis-related genes and the proportion of TICs. Results　 The merged MERGE gene set of GSE12353 and GSE56315 was screened. We obtained 445 (301 up-regulated genes and 143 down-regulated genes) differentially expressed genes； 57 prognosis-related genes( 17 negatively and 40 pos⁃ itively correlated) were obtained from the GSE87371 dataset, and the 301 differentially up-regulated genes and the 17 neg⁃ atively correlated genes were intersected to obtain membrane linked protein 1 (ANXA1), which was a DLBCL prognosisassociated gene. Survival analysis suggested a 5-year OS rate of 3. 56% (95%CI 1. 17%-10. 7%) in the high ANXA1 ex⁃ pression group and 17. 49%( 95%CI 11. 8%-29. 9%) in the low ANXA1 expression group, suggesting a poor prognosis for DLBCL patients in the high ANXA1 expression group (P<0. 001). ANXA1 was an independent prognostic factor (P< 0. 05) and its expression level was not correlated with clinical parameters of patients (P>0. 05). GSEA functional enrich⁃ ment analysis showed that the ANXA1 high expression group was enriched in chemokine signalling pathway, MAPK signal⁃ ling pathway, ECM receptor interaction and JAK-STAT signalling pathway. Immuno-infiltration analysis showed that T cells (49%) and macrophages (31%) were more predominant in DLBCL tissues, and ANXA1 expression was positively correlated with macrophage M2, plasma cells, activated CD4+ memory T cells, CD8+T cells, and γδ T cells. Conclu⁃ sion　 ANXA1 is associated with the prognosis of DLBCL patients, and its high expression is related to the poor prognosis and the proportion of TICs； the enrichment signal pathway mainly includes tumor-related signaling pathways such as the chemokines signaling pathway. [ABSTRACT FROM AUTHOR]

Triple-negative breast cancer (TNBC) is characterized by a more aggressive clinical course with extensive inter- and intra-tumour heterogeneity. Combination of single-cell and bulk tissue transcriptome profiling allows the characterization of tumour heterogeneity and identifies the association of the immune landscape with clinical outcomes. We identified inter- and intra-tumour heterogeneity at a single-cell resolution. Tumour cells shared a high correlation amongst stemness, angiogenesis, and EMT in TNBC. A subset of cells with concurrent high EMT, stemness and angiogenesis was identified at the single-cell level. Amongst tumour-infiltrating immune cells, M2-like tumour-associated macrophages (TAMs) made up the majority of macrophages and displayed immunosuppressive characteristics. CIBERSORT was applied to estimate the abundance of M2-like TAM in bulk tissue transcriptome file from The Cancer Genome Atlas (TCGA). M2-like TAMs were associated with unfavourable prognosis in TNBC patients. A TAM-related gene signature serves as a promising marker for predicting prognosis and response to immunotherapy. Two commonly used machine learning methods, random forest and SVM, were applied to find the genes that were mostly associated with M2-like TAM densities in the gene signature. A neural network-based deep learning framework based on the TAM-related gene signature exhibits high accuracy in predicting the immunotherapy response. [ABSTRACT FROM AUTHOR]

B7-H3 has emerged as a promising target for cancer immunotherapy. We assessed the role of B7-H3 expression in tumour-infiltrating immune cells in non–small-cell lung cancer (NSCLC). Tumour-infiltrating immune cell characterisation was performed by flow cytometry in a prospective cohort, whereas the relationship between B7-H3 expression and clinicopathological features was explored in a retrospective cohort. B7-H3 expression was detected in tumour/epithelial cells and immune cells, including macrophages, monocytes, dendritic cells (DCs) and myeloid-derived suppressor cells. B7-H3 was expressed at higher levels in cells within the tumour than in cells within non-neoplastic tissues. B7-H3 expression score in tumour cells positively correlated with the amount of CD45+ immune cells (rho = 0.305, P = 0.010), CD8+ T-cells (rho = 0.330, P = 0.005), and the percentage of CD8+/CD3+ T-cells (rho = 0.403, P < 0.001). Patients with high tumoural B7-H3 expression showed increased numbers of immune cells (P = 0.002), CD8+ T-cells (P = 0.011), natural killer cells (P = 0.073) and plasmacytoid DCs (P = 0.015). Tumoural B7-H3 expression was higher in males, smokers, squamous cell carcinomas, tumours with wild-type EGFR , poor differentiation, larger size and nodal metastasis (P < 0.05, all). Tumoural B7-H3 expression was associated with PD-L1 expression (P = 0.001), shorter 5-year overall survival (P = 0.012) and poor survival after anti–PD-1 blockade (P = 0.026). Tumoural B7-H3 overexpression was associated with increased tumour-infiltrating cytotoxic lymphocytes and poor prognosis in NSCLC. Thus, B7-H3 is a promising prognostic biomarker and immunotherapeutic target in NSCLC. • B7-H3–related tumour immune microenvironment was comprehensively analysed in non–small-cell lung cancer (NSCLC). • B7-H3 expression is higher in cells within tumour than those within non-neoplastic tissue. • NSCLC with B7-H3 overexpression was highly infiltrated by cytotoxic lymphoid cells and antigen presenting cells. • B7-H3 overexpression was associated with adverse clinicopathological feature in NSCLC. • B7-H3 overexpression was associated with poor prognosis in patients with resected NSCLC or in those received PD-1 blockade. [ABSTRACT FROM AUTHOR]

High mortality of patients with cervical cancer (CC) stresses the imperative of prognostic biomarkers for CC patients. Additionally, the vital status of post‐translational modifications (PTMs) in the progression of cancers has been reported by numerous researches. Therefore, the purpose of this research was to dig a prognostic signature correlated with PTMs for CC. We built a five‐mRNA (GALNTL6, ARSE, DPAGT1, GANAB and FURIN) prognostic signature associated with PTMs to predict both disease‐free survival (DFS) (hazard ratio [HR] = 3.967, 95% CI = 1.985‐7.927; P <.001) and overall survival (HR = 2.092, 95% CI = 1.138‐3.847; P =.018) for CC using data from The Cancer Genome Atlas database. Then, the robustness of the signature was validated using GSE44001 and the Human Protein Atlas (HPA) database. CIBERSORT algorithm analysis displayed that activated CD4 memory T cell was also an independent indicator for DFS (HR = 0.426, 95% CI = 0.186‐0.978; P =.044) which could add additional prognostic value to the signature. Collectively, the PTM‐related signature and activated CD4 memory T cell can provide new avenues for the prognostic predication of CC. These findings give further insights into effective treatment strategies for CC, providing opportunities for further experimental and clinical validations. [ABSTRACT FROM AUTHOR]

A cancer cell-centric view has long dominated the field of cancer biology. Research efforts have focussed on aberrant cancer cell signalling pathways and on changes to cancer cell DNA. Mounting evidence demonstrates that many cancer-associated cell types within the tumour stroma co-evolve and support tumour growth and development, greatly modifying cancer cell behaviour, facilitating invasion and metastasis and controlling dormancy and sensitivity to drug therapy. Thus, these stromal cells represent potential targets for cancer therapy. Among these cell types, immune cells have emerged as a promising target for therapy. The adaptive and the innate immune system play an important role in normal mammary development and breast cancer. The number of infiltrating adaptive immune system cells with tumour-rejecting capacity, primarily, T lymphocytes, is lower in breast cancer compared with other cancer types, but infiltration occurs in a large proportion of cases. There is strong evidence demonstrating the importance of the immunosuppressive role of the innate immune system during breast cancer progression. A consideration of components of both the innate and the adaptive immune system is essential for the design and development of immunotherapies in breast cancer. In this review, we focus on the importance of immunosuppressive myeloidderived suppressor cells (MDSCs) as potential targets for breast cancer therapy. [ABSTRACT FROM AUTHOR]

Introduction: Immune checkpoint therapy (ICIs) effectively improves the prognosis of advanced (stage III/IV) hepatocellular carcinoma (HCC) patients. However, its objective response rate (ORR) is below 20%, significantly limiting ICI use in advanced HCC patients. The level of tumour immune infiltration influences ICI response rate. Recent studies have found ubiquitinase to be an important factor that regulates tumour immune infiltration. Therefore, the aim of this study is to explore the key ubiquitination genes that regulate immune infiltration in advanced HCC and further validate them., Methods: A biotechnological process was performed as a means of classifying 90 advanced HCC patients into three immune subtypes and identifying associations with immune infiltration in the co-expressed modules. Ubiquitination-related genes were then screened with WGCNA. Gene enrichment analysis was performed for the target module and 30 hub genes were screened out by protein-protein interaction network (PPI). ssGSEA, single-gene sequencing and the MCP counter were used for exploring immune infiltration. TIDE score was applied for predicting drug efficacy and GSEA was used for exploring potential pathways. Finally, GRB2 expression in HCC tissue was validated by in vitro experiments., Results: GRB2 expression was found to have a significant correlation with the pathological stage and prognosis of HCC patients and a positive correlation with immune infiltration and tumour mutation burden (TMB). In addition, significant correlations with the efficacy of ICIs, sorafenib and transarterial chemoembolization (TACE) were identified. GRB2 was found to be most significantly associated with the JAK-STAT signalling pathway and cytosolic DNA sensing pathway. Finally, it was found that GRB2 expression is closely related to the prognosis, tumour size and TMN stage., Conclusion: A significant association was observed between the ubiquitinated gene GRB2 and the prognosis and immune infiltration of advanced HCC patients and it may potentially be used for predicting therapy efficacy in advanced HCC patients in the future., Competing Interests: All the authors declare that they have no competing interests., (© 2023 Tang et al.)

Based on a large cohort of patients ( I n i = 282), Rodrigues and colleagues suggest that the nature of MCL ecosystem could influence tumour progression. Ecosystem integration, B-cell lymphomas, tumour-infiltrating immune cells Keywords: ecosystem integration; B-cell lymphomas; tumour-infiltrating immune cells EN ecosystem integration B-cell lymphomas tumour-infiltrating immune cells 447 448 2 05/03/21 20210501 NES 210501 In this issue of BJH, Rodrigues I et al i . investigate how tumour-infiltrating immune cells correlated with the clinical outcome of mantle cell lymphoma (MCL), a rare but often aggressive subtype of non-Hodgkin lymphoma. [Extracted from the article]

Prefoldin complex subunits (PFDNs) and prefoldin-like complex subunits (PFDLNs) collaborate in protein folding, modulate endoplasmic reticulum stress. The association between PFDN/PFDLN and the immune microenvironment of HCC remains unclear. We investigated the biological significance of PFDNs and PFDLNs in HCC using bioinformatics. The relationship between PFDNs/PFDLNs and HCC was analysed using TCGA, and Human Protein Atlas. The protein–protein interaction (PPI) network was performed through String and Cytoscape. In addition, mutations in PFDNs and PFDLNs were analysed using cBioPortal. Clinical correlation analysis, survival analysis was conducted by using UALCAN and Kaplan–Meier analysis. The protein-protein interaction (PPI) network was performed through String and Cytoscape. The GO and KEGG enrichment analyses were also carried out. CCK-8 and Flow cytometry analysis were used to detect the proliferation and apoptosis of PFDN1 and UXT knockdown HCC cells. Immune infiltrates analyses was were conducted using the TIMER and TISIDB to determine whether PFDNs/PFDLNs are predictive biomarkers of immune cell infiltration. We observed that PFDNs and PFDLNs were significantly overexpressed in HCC tissues compared to normal liver tissues. This abnormal expression was associated with worse clinicopathological features and negatively affected patient survival. PFDNs and PFDLNs have varying degrees of mutations in HCC, which may be related to their abnormal expression. In addition, up-regulated PFDN1 and UXT were found to promote HCC proliferation and inhibit apoptosis in vitro. Finally, the expression of certain PFDNs and PFDLNs in the tumour microenvironment was positively correlated with the level of tumour-infiltrating immune cells and significantly enhanced the infiltration of immune cells in the microenvironment. PFDNs and PFDLNs are valuable predictive biomarkers for immune infiltration in HCC and may assist in tumour immunotherapy research and prognosis prediction in the future. [ABSTRACT FROM AUTHOR]

Urothelial carcinoma (UC) is the most common form of bladder cancer. Although the 5-year overall survival rate of bladder cancer is 73%, the outcome for patients with metastatic UC remains poor. Programmed death ligand 1 (PD-L1) is over-expressed by many cancers and facilitates tumour evasion of host immune responses via the PDL1/PD-1 checkpoint. Immunotherapy is an emerging paradigm for the treatment of advanced UC with recent clinical trials demonstrating significant responses in patients by blocking PD-1/PD-L1. Nonetheless, the data on the prevalence of PD-L1 in urothelial tumours is limited. The goal of this study was to evaluate the prevalence of PD-L1 expression in tumour-infiltrating immune cells (IC) in UC in Canada and to correlate its expression with multiple clinical and pathological parameters. Three hundred archived UC specimens from six Canadian sites were assessed for PD-L1 expression using the Ventana PD-L1 (SP142) immunohistochemistry assay. The presence of discernible PD-L1 signal in tumour-infiltrating IC involving >5% of tumour with associated stroma was deemed "positive" and was observed in 39% (CI 33.13-44.43%) of specimens tested. There was no relationship between positivity of the PD-L1 assay and several clinicopathological parameters, including age, gender, and tumour location. Notably, PD-L1 expression of tumourinfiltrating IC exhibited a significant association with tumour stage (p=0.0409), with a trend towards higher PDL1 positivity in more advanced tumours. In conclusion, PD-L1 expression in tumour-infiltrating IC is common in UC in Canada and may be associated with more advanced stage cancers, reinforcing that PD-L1 may be a relevant therapeutic target for UC. [ABSTRACT FROM AUTHOR]